机械科学与技术2012，Vol.31Issue(5)：726-730,5.
基于盲源分离与小波降噪的旋转机械故障分析
Analysis of Rotating Machine Fault Diagnosis Based on Blind Source Separation and Wavelet De-noising
王元生 1任舒心 1杨永锋 1何尚文 1邓旺群2
作者信息
- 1. 西北工业大学振动工程研究所,西安710072
- 2. 中国航空动力机械研究所,株洲412002
- 折叠
摘要
Abstract
The vibration signals of rotating machinery are separated and diagnosed by combining the wavelet noise reduction and the blind source separation in this paper. Firstly, the combing method uses the better wavelet threshold value de-noising to reduce noise for non-stationary vibration signals, and then separates the useful vibration signals with blind source separation. It shows that the combining method is more effective than the direct blind source separation in signal processing. Applying the combining method to analyze real measured trouble signals of a gas turbine, the fault diagnosis results are found to be in agreement with practice. The result shows that the combing method is efficient in analyzing the fault diagnosis of rotating machinery.关键词
故障诊断/盲源分离/小波阀值/旋转机械Key words
fault diagnosis/blind source separation/wavelet threshold/rotating machine分类
信息技术与安全科学引用本文复制引用
王元生,任舒心,杨永锋,何尚文,邓旺群..基于盲源分离与小波降噪的旋转机械故障分析[J].机械科学与技术,2012,31(5):726-730,5.
